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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationFri, 11 Dec 2009 07:25:06 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/11/t12605415663cq77u72ijtnprf.htm/, Retrieved Mon, 29 Apr 2024 04:49:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66234, Retrieved Mon, 29 Apr 2024 04:49:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordssdws paper
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendency] [2009-12-11 14:25:06] [2d672adbf8ae6977476cb9852ecac1a3] [Current]
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Dataseries X:
-1683.85608706230 
-6999.35087749223 
3931.32652673605 
1822.75271017275 
1412.85831010682 
341.612129794388 
-9381.55507514847 
649.055948328826 
1377.63729026095 
-7846.62135114955 
5098.26277502930 
4768.34811151406 
10740.5901250635 
-3118.87364267085 
-6653.8909673415 
-12172.3430680778 
1308.85607902947 
3886.70335197895 
-296.995134388884 
1185.3316058715 
-3756.67652699999 
-2029.93703138424 
-6049.80708904876 
-155.869195324281 
-8288.29444857815 
579.977007038197 
1553.52404432216 
-785.985112768088 
-1164.46843095385 
-3530.73252748869 
3994.02389637401 
5628.36174903917 
-2536.24819950515 
-8281.44574137424 
-4045.3675548633 
-3055.43106194414 
-15078.6790675691 
-4042.4923457908 
-5639.19325606102 
8410.26835938425 
-5007.38028583601 
-6462.30324482812 
1106.39886423720 
-6829.95884874971 
-11713.0921878395 
7497.4340368301 
5293.56561524665 
-16151.1360566203 
6574.13330938066 
4743.47649440836 
9426.5615899051 
-2156.25032128639 
-3480.89311636835 
-3670.22315983447 
3783.98461069648 
-8502.36327823036 
12159.7792426378 
-3389.0226392966 
-4940.13188753005 
-4001.48918672872 
4676.19415638844 
12887.1486085950 
10532.7380857177 
5992.8583735267 
5855.2650302122 
10655.6662177593 
85.964117531585 
-3652.4610889491 
3167.26625859986 
-3333.15438338008 
353.444090633532 
-6120.35884515823 
-2534.37536122279 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66234&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66234&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66234&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-644.621081677988735.526516714735-0.8764076712791
Geometric MeanNaN
Harmonic Mean7599.28208526315
Quadratic Mean6274.35118780105
Winsorized Mean ( 1 / 24 )-639.893853964372728.865640716097-0.877931155234163
Winsorized Mean ( 2 / 24 )-599.150103774865699.601495583506-0.856416270630098
Winsorized Mean ( 3 / 24 )-583.766803517299694.547898123264-0.840498985159546
Winsorized Mean ( 4 / 24 )-462.747133344728666.89100604799-0.693887200679129
Winsorized Mean ( 5 / 24 )-478.294030529282639.202395033444-0.748266956202905
Winsorized Mean ( 6 / 24 )-544.230282655472618.746079602584-0.879569666130291
Winsorized Mean ( 7 / 24 )-631.105615634262601.612876101695-1.04902278641985
Winsorized Mean ( 8 / 24 )-684.637269028755574.900462626852-1.19087966271672
Winsorized Mean ( 9 / 24 )-651.843298614642545.043392685035-1.19594752888111
Winsorized Mean ( 10 / 24 )-647.487314309434538.137820385611-1.20319979340137
Winsorized Mean ( 11 / 24 )-655.147443041119528.234686296263-1.24025827920296
Winsorized Mean ( 12 / 24 )-678.688551744539514.305462734254-1.31962151079702
Winsorized Mean ( 13 / 24 )-652.574301431073499.330860326713-1.30689759692420
Winsorized Mean ( 14 / 24 )-702.315132988344487.275865758379-1.44130908657930
Winsorized Mean ( 15 / 24 )-623.0530338345473.839621885444-1.31490277523717
Winsorized Mean ( 16 / 24 )-499.320292529275451.715226708457-1.10538733920418
Winsorized Mean ( 17 / 24 )-642.521274023028424.83162323674-1.51241395150328
Winsorized Mean ( 18 / 24 )-437.354077659765392.840214357747-1.11331289841289
Winsorized Mean ( 19 / 24 )-448.219986536579390.953457642973-1.1464791467477
Winsorized Mean ( 20 / 24 )-465.128365227096385.197188903017-1.20750716419222
Winsorized Mean ( 21 / 24 )-572.114934264435349.455021635758-1.63716329382371
Winsorized Mean ( 22 / 24 )-951.256358754229288.664130029712-3.29537431150977
Winsorized Mean ( 23 / 24 )-1030.48555990765276.765964998629-3.72331027015102
Winsorized Mean ( 24 / 24 )-1036.71147971749265.56095035708-3.90385513503964
Trimmed Mean ( 1 / 24 )-616.807767809406697.779803590037-0.883957610461016
Trimmed Mean ( 2 / 24 )-592.38335781937660.583119760035-0.896758242981687
Trimmed Mean ( 3 / 24 )-588.69699621675635.330170064725-0.926600095438212
Trimmed Mean ( 4 / 24 )-590.542658099108607.39187733567-0.972259722486789
Trimmed Mean ( 5 / 24 )-627.56279027002584.321510762718-1.07400254604842
Trimmed Mean ( 6 / 24 )-663.289411453869565.505764992475-1.17291361558922
Trimmed Mean ( 7 / 24 )-687.841152703256548.615616552147-1.25377610835450
Trimmed Mean ( 8 / 24 )-698.221338683298532.550361180099-1.31108978526666
Trimmed Mean ( 9 / 24 )-700.475059330529519.419423271085-1.34857309516697
Trimmed Mean ( 10 / 24 )-707.917655834218509.993109778284-1.38809258843120
Trimmed Mean ( 11 / 24 )-716.567489032864499.512570158136-1.43453344688806
Trimmed Mean ( 12 / 24 )-724.885973925994488.274211656296-1.48458787423378
Trimmed Mean ( 13 / 24 )-730.865427506218476.847366798973-1.53270307942024
Trimmed Mean ( 14 / 24 )-740.635089392518465.24310202316-1.59193137130199
Trimmed Mean ( 15 / 24 )-745.281861514619452.65069771103-1.64648340383296
Trimmed Mean ( 16 / 24 )-759.790323987218438.922368011908-1.73103578072058
Trimmed Mean ( 17 / 24 )-790.26197830842425.504785507363-1.8572340552319
Trimmed Mean ( 18 / 24 )-807.408355753307413.910538926211-1.95068325113907
Trimmed Mean ( 19 / 24 )-850.287660992717405.006977966332-2.09943953376379
Trimmed Mean ( 20 / 24 )-897.099367907068392.272549697821-2.28692874022954
Trimmed Mean ( 21 / 24 )-947.960469835516375.119954526258-2.52708622507887
Trimmed Mean ( 22 / 24 )-993.012561948306361.275268788475-2.74863143906402
Trimmed Mean ( 23 / 24 )-998.144216549598359.814355506321-2.77405334521753
Trimmed Mean ( 24 / 24 )-994.038272088489358.999910860283-2.76890952342145
Median-785.985112768088
Midrange-1631.99372401265
Midmean - Weighted Average at Xnp-939.0398802669
Midmean - Weighted Average at X(n+1)p-807.408355753306
Midmean - Empirical Distribution Function-807.408355753306
Midmean - Empirical Distribution Function - Averaging-807.408355753306
Midmean - Empirical Distribution Function - Interpolation-807.408355753306
Midmean - Closest Observation-916.164238168484
Midmean - True Basic - Statistics Graphics Toolkit-807.408355753306
Midmean - MS Excel (old versions)-807.408355753306
Number of observations73

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -644.621081677988 & 735.526516714735 & -0.8764076712791 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 7599.28208526315 &  &  \tabularnewline
Quadratic Mean & 6274.35118780105 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & -639.893853964372 & 728.865640716097 & -0.877931155234163 \tabularnewline
Winsorized Mean ( 2 / 24 ) & -599.150103774865 & 699.601495583506 & -0.856416270630098 \tabularnewline
Winsorized Mean ( 3 / 24 ) & -583.766803517299 & 694.547898123264 & -0.840498985159546 \tabularnewline
Winsorized Mean ( 4 / 24 ) & -462.747133344728 & 666.89100604799 & -0.693887200679129 \tabularnewline
Winsorized Mean ( 5 / 24 ) & -478.294030529282 & 639.202395033444 & -0.748266956202905 \tabularnewline
Winsorized Mean ( 6 / 24 ) & -544.230282655472 & 618.746079602584 & -0.879569666130291 \tabularnewline
Winsorized Mean ( 7 / 24 ) & -631.105615634262 & 601.612876101695 & -1.04902278641985 \tabularnewline
Winsorized Mean ( 8 / 24 ) & -684.637269028755 & 574.900462626852 & -1.19087966271672 \tabularnewline
Winsorized Mean ( 9 / 24 ) & -651.843298614642 & 545.043392685035 & -1.19594752888111 \tabularnewline
Winsorized Mean ( 10 / 24 ) & -647.487314309434 & 538.137820385611 & -1.20319979340137 \tabularnewline
Winsorized Mean ( 11 / 24 ) & -655.147443041119 & 528.234686296263 & -1.24025827920296 \tabularnewline
Winsorized Mean ( 12 / 24 ) & -678.688551744539 & 514.305462734254 & -1.31962151079702 \tabularnewline
Winsorized Mean ( 13 / 24 ) & -652.574301431073 & 499.330860326713 & -1.30689759692420 \tabularnewline
Winsorized Mean ( 14 / 24 ) & -702.315132988344 & 487.275865758379 & -1.44130908657930 \tabularnewline
Winsorized Mean ( 15 / 24 ) & -623.0530338345 & 473.839621885444 & -1.31490277523717 \tabularnewline
Winsorized Mean ( 16 / 24 ) & -499.320292529275 & 451.715226708457 & -1.10538733920418 \tabularnewline
Winsorized Mean ( 17 / 24 ) & -642.521274023028 & 424.83162323674 & -1.51241395150328 \tabularnewline
Winsorized Mean ( 18 / 24 ) & -437.354077659765 & 392.840214357747 & -1.11331289841289 \tabularnewline
Winsorized Mean ( 19 / 24 ) & -448.219986536579 & 390.953457642973 & -1.1464791467477 \tabularnewline
Winsorized Mean ( 20 / 24 ) & -465.128365227096 & 385.197188903017 & -1.20750716419222 \tabularnewline
Winsorized Mean ( 21 / 24 ) & -572.114934264435 & 349.455021635758 & -1.63716329382371 \tabularnewline
Winsorized Mean ( 22 / 24 ) & -951.256358754229 & 288.664130029712 & -3.29537431150977 \tabularnewline
Winsorized Mean ( 23 / 24 ) & -1030.48555990765 & 276.765964998629 & -3.72331027015102 \tabularnewline
Winsorized Mean ( 24 / 24 ) & -1036.71147971749 & 265.56095035708 & -3.90385513503964 \tabularnewline
Trimmed Mean ( 1 / 24 ) & -616.807767809406 & 697.779803590037 & -0.883957610461016 \tabularnewline
Trimmed Mean ( 2 / 24 ) & -592.38335781937 & 660.583119760035 & -0.896758242981687 \tabularnewline
Trimmed Mean ( 3 / 24 ) & -588.69699621675 & 635.330170064725 & -0.926600095438212 \tabularnewline
Trimmed Mean ( 4 / 24 ) & -590.542658099108 & 607.39187733567 & -0.972259722486789 \tabularnewline
Trimmed Mean ( 5 / 24 ) & -627.56279027002 & 584.321510762718 & -1.07400254604842 \tabularnewline
Trimmed Mean ( 6 / 24 ) & -663.289411453869 & 565.505764992475 & -1.17291361558922 \tabularnewline
Trimmed Mean ( 7 / 24 ) & -687.841152703256 & 548.615616552147 & -1.25377610835450 \tabularnewline
Trimmed Mean ( 8 / 24 ) & -698.221338683298 & 532.550361180099 & -1.31108978526666 \tabularnewline
Trimmed Mean ( 9 / 24 ) & -700.475059330529 & 519.419423271085 & -1.34857309516697 \tabularnewline
Trimmed Mean ( 10 / 24 ) & -707.917655834218 & 509.993109778284 & -1.38809258843120 \tabularnewline
Trimmed Mean ( 11 / 24 ) & -716.567489032864 & 499.512570158136 & -1.43453344688806 \tabularnewline
Trimmed Mean ( 12 / 24 ) & -724.885973925994 & 488.274211656296 & -1.48458787423378 \tabularnewline
Trimmed Mean ( 13 / 24 ) & -730.865427506218 & 476.847366798973 & -1.53270307942024 \tabularnewline
Trimmed Mean ( 14 / 24 ) & -740.635089392518 & 465.24310202316 & -1.59193137130199 \tabularnewline
Trimmed Mean ( 15 / 24 ) & -745.281861514619 & 452.65069771103 & -1.64648340383296 \tabularnewline
Trimmed Mean ( 16 / 24 ) & -759.790323987218 & 438.922368011908 & -1.73103578072058 \tabularnewline
Trimmed Mean ( 17 / 24 ) & -790.26197830842 & 425.504785507363 & -1.8572340552319 \tabularnewline
Trimmed Mean ( 18 / 24 ) & -807.408355753307 & 413.910538926211 & -1.95068325113907 \tabularnewline
Trimmed Mean ( 19 / 24 ) & -850.287660992717 & 405.006977966332 & -2.09943953376379 \tabularnewline
Trimmed Mean ( 20 / 24 ) & -897.099367907068 & 392.272549697821 & -2.28692874022954 \tabularnewline
Trimmed Mean ( 21 / 24 ) & -947.960469835516 & 375.119954526258 & -2.52708622507887 \tabularnewline
Trimmed Mean ( 22 / 24 ) & -993.012561948306 & 361.275268788475 & -2.74863143906402 \tabularnewline
Trimmed Mean ( 23 / 24 ) & -998.144216549598 & 359.814355506321 & -2.77405334521753 \tabularnewline
Trimmed Mean ( 24 / 24 ) & -994.038272088489 & 358.999910860283 & -2.76890952342145 \tabularnewline
Median & -785.985112768088 &  &  \tabularnewline
Midrange & -1631.99372401265 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -939.0398802669 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -807.408355753306 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -807.408355753306 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -807.408355753306 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -807.408355753306 &  &  \tabularnewline
Midmean - Closest Observation & -916.164238168484 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -807.408355753306 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -807.408355753306 &  &  \tabularnewline
Number of observations & 73 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66234&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]-644.621081677988[/C][C]735.526516714735[/C][C]-0.8764076712791[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]7599.28208526315[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]6274.35118780105[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]-639.893853964372[/C][C]728.865640716097[/C][C]-0.877931155234163[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]-599.150103774865[/C][C]699.601495583506[/C][C]-0.856416270630098[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]-583.766803517299[/C][C]694.547898123264[/C][C]-0.840498985159546[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]-462.747133344728[/C][C]666.89100604799[/C][C]-0.693887200679129[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]-478.294030529282[/C][C]639.202395033444[/C][C]-0.748266956202905[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]-544.230282655472[/C][C]618.746079602584[/C][C]-0.879569666130291[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]-631.105615634262[/C][C]601.612876101695[/C][C]-1.04902278641985[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]-684.637269028755[/C][C]574.900462626852[/C][C]-1.19087966271672[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]-651.843298614642[/C][C]545.043392685035[/C][C]-1.19594752888111[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]-647.487314309434[/C][C]538.137820385611[/C][C]-1.20319979340137[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]-655.147443041119[/C][C]528.234686296263[/C][C]-1.24025827920296[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]-678.688551744539[/C][C]514.305462734254[/C][C]-1.31962151079702[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]-652.574301431073[/C][C]499.330860326713[/C][C]-1.30689759692420[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]-702.315132988344[/C][C]487.275865758379[/C][C]-1.44130908657930[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]-623.0530338345[/C][C]473.839621885444[/C][C]-1.31490277523717[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]-499.320292529275[/C][C]451.715226708457[/C][C]-1.10538733920418[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]-642.521274023028[/C][C]424.83162323674[/C][C]-1.51241395150328[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]-437.354077659765[/C][C]392.840214357747[/C][C]-1.11331289841289[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]-448.219986536579[/C][C]390.953457642973[/C][C]-1.1464791467477[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]-465.128365227096[/C][C]385.197188903017[/C][C]-1.20750716419222[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]-572.114934264435[/C][C]349.455021635758[/C][C]-1.63716329382371[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]-951.256358754229[/C][C]288.664130029712[/C][C]-3.29537431150977[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]-1030.48555990765[/C][C]276.765964998629[/C][C]-3.72331027015102[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]-1036.71147971749[/C][C]265.56095035708[/C][C]-3.90385513503964[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]-616.807767809406[/C][C]697.779803590037[/C][C]-0.883957610461016[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]-592.38335781937[/C][C]660.583119760035[/C][C]-0.896758242981687[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]-588.69699621675[/C][C]635.330170064725[/C][C]-0.926600095438212[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]-590.542658099108[/C][C]607.39187733567[/C][C]-0.972259722486789[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]-627.56279027002[/C][C]584.321510762718[/C][C]-1.07400254604842[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]-663.289411453869[/C][C]565.505764992475[/C][C]-1.17291361558922[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]-687.841152703256[/C][C]548.615616552147[/C][C]-1.25377610835450[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]-698.221338683298[/C][C]532.550361180099[/C][C]-1.31108978526666[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]-700.475059330529[/C][C]519.419423271085[/C][C]-1.34857309516697[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]-707.917655834218[/C][C]509.993109778284[/C][C]-1.38809258843120[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]-716.567489032864[/C][C]499.512570158136[/C][C]-1.43453344688806[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]-724.885973925994[/C][C]488.274211656296[/C][C]-1.48458787423378[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]-730.865427506218[/C][C]476.847366798973[/C][C]-1.53270307942024[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]-740.635089392518[/C][C]465.24310202316[/C][C]-1.59193137130199[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]-745.281861514619[/C][C]452.65069771103[/C][C]-1.64648340383296[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]-759.790323987218[/C][C]438.922368011908[/C][C]-1.73103578072058[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]-790.26197830842[/C][C]425.504785507363[/C][C]-1.8572340552319[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]-807.408355753307[/C][C]413.910538926211[/C][C]-1.95068325113907[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]-850.287660992717[/C][C]405.006977966332[/C][C]-2.09943953376379[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]-897.099367907068[/C][C]392.272549697821[/C][C]-2.28692874022954[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]-947.960469835516[/C][C]375.119954526258[/C][C]-2.52708622507887[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]-993.012561948306[/C][C]361.275268788475[/C][C]-2.74863143906402[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]-998.144216549598[/C][C]359.814355506321[/C][C]-2.77405334521753[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]-994.038272088489[/C][C]358.999910860283[/C][C]-2.76890952342145[/C][/ROW]
[ROW][C]Median[/C][C]-785.985112768088[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-1631.99372401265[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-939.0398802669[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-916.164238168484[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-807.408355753306[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]73[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66234&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66234&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-644.621081677988735.526516714735-0.8764076712791
Geometric MeanNaN
Harmonic Mean7599.28208526315
Quadratic Mean6274.35118780105
Winsorized Mean ( 1 / 24 )-639.893853964372728.865640716097-0.877931155234163
Winsorized Mean ( 2 / 24 )-599.150103774865699.601495583506-0.856416270630098
Winsorized Mean ( 3 / 24 )-583.766803517299694.547898123264-0.840498985159546
Winsorized Mean ( 4 / 24 )-462.747133344728666.89100604799-0.693887200679129
Winsorized Mean ( 5 / 24 )-478.294030529282639.202395033444-0.748266956202905
Winsorized Mean ( 6 / 24 )-544.230282655472618.746079602584-0.879569666130291
Winsorized Mean ( 7 / 24 )-631.105615634262601.612876101695-1.04902278641985
Winsorized Mean ( 8 / 24 )-684.637269028755574.900462626852-1.19087966271672
Winsorized Mean ( 9 / 24 )-651.843298614642545.043392685035-1.19594752888111
Winsorized Mean ( 10 / 24 )-647.487314309434538.137820385611-1.20319979340137
Winsorized Mean ( 11 / 24 )-655.147443041119528.234686296263-1.24025827920296
Winsorized Mean ( 12 / 24 )-678.688551744539514.305462734254-1.31962151079702
Winsorized Mean ( 13 / 24 )-652.574301431073499.330860326713-1.30689759692420
Winsorized Mean ( 14 / 24 )-702.315132988344487.275865758379-1.44130908657930
Winsorized Mean ( 15 / 24 )-623.0530338345473.839621885444-1.31490277523717
Winsorized Mean ( 16 / 24 )-499.320292529275451.715226708457-1.10538733920418
Winsorized Mean ( 17 / 24 )-642.521274023028424.83162323674-1.51241395150328
Winsorized Mean ( 18 / 24 )-437.354077659765392.840214357747-1.11331289841289
Winsorized Mean ( 19 / 24 )-448.219986536579390.953457642973-1.1464791467477
Winsorized Mean ( 20 / 24 )-465.128365227096385.197188903017-1.20750716419222
Winsorized Mean ( 21 / 24 )-572.114934264435349.455021635758-1.63716329382371
Winsorized Mean ( 22 / 24 )-951.256358754229288.664130029712-3.29537431150977
Winsorized Mean ( 23 / 24 )-1030.48555990765276.765964998629-3.72331027015102
Winsorized Mean ( 24 / 24 )-1036.71147971749265.56095035708-3.90385513503964
Trimmed Mean ( 1 / 24 )-616.807767809406697.779803590037-0.883957610461016
Trimmed Mean ( 2 / 24 )-592.38335781937660.583119760035-0.896758242981687
Trimmed Mean ( 3 / 24 )-588.69699621675635.330170064725-0.926600095438212
Trimmed Mean ( 4 / 24 )-590.542658099108607.39187733567-0.972259722486789
Trimmed Mean ( 5 / 24 )-627.56279027002584.321510762718-1.07400254604842
Trimmed Mean ( 6 / 24 )-663.289411453869565.505764992475-1.17291361558922
Trimmed Mean ( 7 / 24 )-687.841152703256548.615616552147-1.25377610835450
Trimmed Mean ( 8 / 24 )-698.221338683298532.550361180099-1.31108978526666
Trimmed Mean ( 9 / 24 )-700.475059330529519.419423271085-1.34857309516697
Trimmed Mean ( 10 / 24 )-707.917655834218509.993109778284-1.38809258843120
Trimmed Mean ( 11 / 24 )-716.567489032864499.512570158136-1.43453344688806
Trimmed Mean ( 12 / 24 )-724.885973925994488.274211656296-1.48458787423378
Trimmed Mean ( 13 / 24 )-730.865427506218476.847366798973-1.53270307942024
Trimmed Mean ( 14 / 24 )-740.635089392518465.24310202316-1.59193137130199
Trimmed Mean ( 15 / 24 )-745.281861514619452.65069771103-1.64648340383296
Trimmed Mean ( 16 / 24 )-759.790323987218438.922368011908-1.73103578072058
Trimmed Mean ( 17 / 24 )-790.26197830842425.504785507363-1.8572340552319
Trimmed Mean ( 18 / 24 )-807.408355753307413.910538926211-1.95068325113907
Trimmed Mean ( 19 / 24 )-850.287660992717405.006977966332-2.09943953376379
Trimmed Mean ( 20 / 24 )-897.099367907068392.272549697821-2.28692874022954
Trimmed Mean ( 21 / 24 )-947.960469835516375.119954526258-2.52708622507887
Trimmed Mean ( 22 / 24 )-993.012561948306361.275268788475-2.74863143906402
Trimmed Mean ( 23 / 24 )-998.144216549598359.814355506321-2.77405334521753
Trimmed Mean ( 24 / 24 )-994.038272088489358.999910860283-2.76890952342145
Median-785.985112768088
Midrange-1631.99372401265
Midmean - Weighted Average at Xnp-939.0398802669
Midmean - Weighted Average at X(n+1)p-807.408355753306
Midmean - Empirical Distribution Function-807.408355753306
Midmean - Empirical Distribution Function - Averaging-807.408355753306
Midmean - Empirical Distribution Function - Interpolation-807.408355753306
Midmean - Closest Observation-916.164238168484
Midmean - True Basic - Statistics Graphics Toolkit-807.408355753306
Midmean - MS Excel (old versions)-807.408355753306
Number of observations73



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')